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   "source": [
    " # Concise Overview of OpenPNM\n",
    " "
   ]
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   "source": [
    "<h1><span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Creating-a-network\" data-toc-modified-id=\"Creating-a-network-1\">Creating a network</a></span></li><li><span><a href=\"#Quick-visualization-of-topology\" data-toc-modified-id=\"Quick-visualization-of-topology-2\">Quick visualization of topology</a></span></li><li><span><a href=\"#Printing-objects\" data-toc-modified-id=\"Printing-objects-3\">Printing objects</a></span></li><li><span><a href=\"#Adding-geometrical-properties\" data-toc-modified-id=\"Adding-geometrical-properties-4\">Adding geometrical properties</a></span></li><li><span><a href=\"#Adding-pore-scale-models\" data-toc-modified-id=\"Adding-pore-scale-models-5\">Adding pore-scale models</a></span></li><li><span><a href=\"#Adjusting-pore-scale-models\" data-toc-modified-id=\"Adjusting-pore-scale-models-6\">Adjusting pore-scale models</a></span></li><li><span><a href=\"#Inspecting-histograms-of-properties\" data-toc-modified-id=\"Inspecting-histograms-of-properties-7\">Inspecting histograms of properties</a></span></li><li><span><a href=\"#Creating-phases-with-thermophysical-properties\" data-toc-modified-id=\"Creating-phases-with-thermophysical-properties-8\">Creating phases with thermophysical properties</a></span></li><li><span><a href=\"#Adding-static-data\" data-toc-modified-id=\"Adding-static-data-9\">Adding static data</a></span></li><li><span><a href=\"#Using-pre-defined-classes-that-include-pore-scale-models\" data-toc-modified-id=\"Using-pre-defined-classes-that-include-pore-scale-models-10\">Using pre-defined classes that include pore-scale models</a></span></li><li><span><a href=\"#Defining-physics\" data-toc-modified-id=\"Defining-physics-11\">Defining physics</a></span></li><li><span><a href=\"#Overview-of-the-simulation-setup\" data-toc-modified-id=\"Overview-of-the-simulation-setup-12\">Overview of the simulation setup</a></span></li><li><span><a href=\"#Objects-can-have-names\" data-toc-modified-id=\"Objects-can-have-names-13\">Objects can have names</a></span></li><li><span><a href=\"#Running-a-simulation\" data-toc-modified-id=\"Running-a-simulation-14\">Running a simulation</a></span></li><li><span><a href=\"#Performing-a-porosimetry-simulation\" data-toc-modified-id=\"Performing-a-porosimetry-simulation-15\">Performing a porosimetry simulation</a></span></li><li><span><a href=\"#Using-labels-to-find-pore-indices\" data-toc-modified-id=\"Using-labels-to-find-pore-indices-16\">Using labels to find pore indices</a></span></li><li><span><a href=\"#Running-a-fluid-flow-simulation\" data-toc-modified-id=\"Running-a-fluid-flow-simulation-17\">Running a fluid flow simulation</a></span></li><li><span><a href=\"#Altering-the-settings-of-a-simulation\" data-toc-modified-id=\"Altering-the-settings-of-a-simulation-18\">Altering the settings of a simulation</a></span></li><li><span><a href=\"#Estimating-permeability-coefficient-of-a-network\" data-toc-modified-id=\"Estimating-permeability-coefficient-of-a-network-19\">Estimating permeability coefficient of a network</a></span></li><li><span><a href=\"#Returning-results-to-the-phase-object\" data-toc-modified-id=\"Returning-results-to-the-phase-object-20\">Returning results to the phase object</a></span></li><li><span><a href=\"#Outputting-or-saving-simualtion-results\" data-toc-modified-id=\"Outputting-or-saving-simualtion-results-21\">Outputting or saving simualtion results</a></span></li></ul></div>"
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    "import openpnm as op\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "op.Workspace().settings['loglevel'] = 50"
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   "source": [
    "## Creating a network\n",
    "\n",
    "\n",
    "OpenPNM includes several network \"generators\", including the traditional cubic lattice that will be used here.  \n",
    "\n",
    "A set of examples demonstrating the available network generators can be found [here](/examples/notebooks/network/generation)"
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   "source": [
    "For this introduction we'll start by just using a standard cubic network:"
   ]
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    "Lx, Ly, Lz = 4, 6, 8\n",
    "spacing = 1e-4\n",
    "pn = op.network.Cubic(shape=[Lx, Ly, Lz], spacing=spacing)"
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   "source": [
    "## Quick visualization of topology\n",
    "\n",
    "OpenPNM support Paraview for very detailed visualization, but it's possible to get a quick view of a network for inspection within python.  \n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "| [A detailed illustration of OpenPNM's plotting functionality](/examples/notebooks/io/quick_plotting_networks.ipynb)| \n",
    "| [Export to Paraview is the preferred way to visualize a network](/examples/notebooks/io/rendering_in_paraview.ipynb)|\n"
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
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   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "op.topotools.plot_coordinates(network=pn, c='r', s=50, ax=ax)\n",
    "op.topotools.plot_connections(network=pn, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Printing objects\n",
    "\n",
    "One of the most useful development or debugging tools is to ``print`` the network, so see a list of its properties:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:01.352662Z",
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     "iopub.status.idle": "2021-06-24T11:25:01.355589Z",
     "shell.execute_reply": "2021-06-24T11:25:01.354921Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "openpnm.network.Cubic : net_01\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Properties                                    Valid Values\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.coords                                     192 / 192  \n",
      "2     throat.conns                                    472 / 472  \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Labels                                        Assigned Locations\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.all                                      192       \n",
      "2     pore.back                                     32        \n",
      "3     pore.bottom                                   24        \n",
      "4     pore.front                                    32        \n",
      "5     pore.internal                                 192       \n",
      "6     pore.left                                     48        \n",
      "7     pore.right                                    48        \n",
      "8     pore.surface                                  144       \n",
      "9     pore.top                                      24        \n",
      "10    throat.all                                    472       \n",
      "11    throat.internal                               472       \n",
      "12    throat.surface                                284       \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "print(pn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding geometrical properties\n",
    "\n",
    "The network only stores topological information.  Geometry objects are used to store information like pore and throat sizes.  Each simulation should have a geometry object associated with it.  We can create an empty geometry and add properties to it later:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:01.364514Z"
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   "source": [
    "geo = op.geometry.GenericGeometry(network=pn, pores=pn.Ps, throats=pn.Ts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding pore-scale models\n",
    "\n",
    "Pore-scale models are one of the most useful aspects of OpenPNM.\n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "| [In-depth discussion and illustration of pore-scale models](/examples/tutorials/pore_scale_models.ipynb)|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below we'll add a few to ``geo``.  OpenPNM includes a library of pre-written models to choose from.  First assign a random seed to each pore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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     "shell.execute_reply": "2021-06-24T11:25:01.375366Z"
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   "outputs": [],
   "source": [
    "geo.add_model(propname='pore.seed',\n",
    "              model=op.models.geometry.pore_size.random,\n",
    "              seed=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next use the seed to find pore sizes from the cumulative pore size distribution.  This process is described in detail [here](/examples/notebooks/3 - geometry/Playing with Pore Size Distributions.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:01.525065Z"
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   "outputs": [],
   "source": [
    "geo.add_model(propname='pore.diameter',\n",
    "              model=op.models.geometry.pore_size.weibull,\n",
    "              scale=0.5e-4, shape=0.8, loc=1e-6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also add models for pore volume, as well as throat diameter, length, and volume:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:01.539991Z"
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   "outputs": [],
   "source": [
    "geo.add_model(propname='pore.volume',\n",
    "              model=op.models.geometry.pore_volume.sphere)\n",
    "geo.add_model(propname='throat.diameter',\n",
    "              model=op.models.geometry.throat_size.from_neighbor_pores,\n",
    "              mode='min')\n",
    "geo.add_model(propname='throat.length',\n",
    "              model=op.models.geometry.throat_length.classic)\n",
    "geo.add_model(propname='throat.volume',\n",
    "              model=op.models.geometry.throat_volume.cylinder)\n",
    "geo.add_model(propname='throat.hydraulic_size_factors',\n",
    "              model=op.models.geometry.hydraulic_size_factors.spheres_and_cylinders)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adjusting pore-scale models\n",
    "\n",
    "All the models that have been added to an object are stored in the ``models`` attribute, under the same key as the property they calculate.  The parameters of each model are also stored and can be adjusted\n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "| [Adjusting the pore size distribution](/examples/notebooks/geometry/adjusting_pore_size_distributions.ipynb)| "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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     "shell.execute_reply": "2021-06-24T11:25:01.552603Z"
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     "text": [
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#   Property Name                       Parameter                 Value\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1   pore.seed                           model:                    random\n",
      "                                        seed:                     0\n",
      "                                        num_range:                [0, 1]\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "2   pore.diameter                       model:                    weibull\n",
      "                                        scale:                    5e-05\n",
      "                                        shape:                    0.8\n",
      "                                        loc:                      1e-06\n",
      "                                        seeds:                    pore.seed\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "3   pore.volume                         model:                    sphere\n",
      "                                        pore_diameter:            pore.diameter\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "4   throat.diameter                     model:                    from_neighbor_pores\n",
      "                                        mode:                     min\n",
      "                                        prop:                     pore.diameter\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "5   throat.length                       model:                    classic\n",
      "                                        pore_diameter:            pore.diameter\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "6   throat.volume                       model:                    cylinder\n",
      "                                        throat_length:            throat.length\n",
      "                                        throat_diameter:          throat.diameter\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "7   throat.hydraulic_size_factors       model:                    spheres_and_cylinders\n",
      "                                        pore_diameter:            pore.diameter\n",
      "                                        throat_diameter:          throat.diameter\n",
      "                                        regeneration mode:        normal\n",
      "―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "print(geo.models)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:01.563184Z"
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   "source": [
    "geo.models['pore.diameter']['shape'] = 1.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This change is not reflected in the 'pore.diameter' values until ``regenerate_models`` is run.  This process also automatically updates all the values that depend on it like 'pore.volume'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2021-06-24T11:25:01.570501Z",
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     "shell.execute_reply": "2021-06-24T11:25:01.662438Z"
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   },
   "outputs": [],
   "source": [
    "geo.regenerate_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspecting histograms of properties\n",
    "\n",
    "Ideally, [matplotlib](https://realpython.com/python-matplotlib-guide/) should be used to make nice plots of pore size histograms and such, but each OpenPNM object has the ability to plot histograms for quick inspections:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
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   ],
   "source": [
    "geo.show_hist(['pore.diameter', 'throat.diameter', 'throat.length'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating phases with thermophysical properties\n",
    "\n",
    "It's possible to create a blank phase with no properties or pore-scale models. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.047924Z",
     "iopub.status.busy": "2021-06-24T11:25:02.046559Z",
     "iopub.status.idle": "2021-06-24T11:25:02.051926Z",
     "shell.execute_reply": "2021-06-24T11:25:02.050843Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "openpnm.phases.GenericPhase : phase_01\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Properties                                    Valid Values\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.pressure                                   192 / 192  \n",
      "2     pore.temperature                                192 / 192  \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Labels                                        Assigned Locations\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.all                                      192       \n",
      "2     throat.all                                    472       \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "water = op.phases.GenericPhase(network=pn)\n",
    "print(water)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding static data\n",
    "\n",
    "The phase objec created above is empty of all physical properties.  We could add pore-scale models if desired, as done for ``geo``, but we can also add a static value directly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.058363Z",
     "iopub.status.busy": "2021-06-24T11:25:02.057345Z",
     "iopub.status.idle": "2021-06-24T11:25:02.060058Z",
     "shell.execute_reply": "2021-06-24T11:25:02.060855Z"
    }
   },
   "outputs": [],
   "source": [
    "water['pore.viscosity'] = 0.001"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are several important features evidient in the above line. \n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "|[Overview of data storage in OpenPNM](/examples/tutorials/data_and_topology_storage.ipynb)|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using pre-defined classes that include pore-scale models\n",
    "\n",
    "OpenPNM includes a small selection of pre-defined phases which include common pore-scale model and preset parameters for describing their properties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.077364Z",
     "iopub.status.busy": "2021-06-24T11:25:02.076125Z",
     "iopub.status.idle": "2021-06-24T11:25:02.080748Z",
     "shell.execute_reply": "2021-06-24T11:25:02.081880Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "openpnm.phases.Mercury : phase_02\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Properties                                    Valid Values\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.contact_angle                              192 / 192  \n",
      "2     pore.critical_pressure                          192 / 192  \n",
      "3     pore.critical_temperature                       192 / 192  \n",
      "4     pore.critical_volume                            192 / 192  \n",
      "5     pore.density                                    192 / 192  \n",
      "6     pore.diffusivity                                192 / 192  \n",
      "7     pore.electrical_conductivity                    192 / 192  \n",
      "8     pore.molar_density                              192 / 192  \n",
      "9     pore.molecular_weight                           192 / 192  \n",
      "10    pore.pressure                                   192 / 192  \n",
      "11    pore.surface_tension                            192 / 192  \n",
      "12    pore.temperature                                192 / 192  \n",
      "13    pore.thermal_conductivity                       192 / 192  \n",
      "14    pore.vapor_pressure                             192 / 192  \n",
      "15    pore.viscosity                                  192 / 192  \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "#     Labels                                        Assigned Locations\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "1     pore.all                                      192       \n",
      "2     throat.all                                    472       \n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "hg = op.phases.Mercury(network=pn)\n",
    "print(hg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Defining physics\n",
    "\n",
    "The last step of the 'setup' of an OpenPNM simulation involves defining which pore-scale physics to use in algorithms.  For capillary pressure curves, for instance, we need to calcuate the entry pressure of each throat.  This is often doen using the Washburn equation.\n",
    "\n",
    "These pore-scale models are applied to a physics object.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.093986Z",
     "iopub.status.busy": "2021-06-24T11:25:02.092623Z",
     "iopub.status.idle": "2021-06-24T11:25:02.097033Z",
     "shell.execute_reply": "2021-06-24T11:25:02.095787Z"
    }
   },
   "outputs": [],
   "source": [
    "phys = op.physics.GenericPhysics(network=pn, phase=hg, geometry=geo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.106285Z",
     "iopub.status.busy": "2021-06-24T11:25:02.104918Z",
     "iopub.status.idle": "2021-06-24T11:25:02.114711Z",
     "shell.execute_reply": "2021-06-24T11:25:02.115944Z"
    }
   },
   "outputs": [],
   "source": [
    "phys.add_model(propname='throat.entry_pressure',\n",
    "               model=op.models.physics.capillary_pressure.washburn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview of the simulation setup\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Physics objects require know to which phase *and* geometry they belong.  This is because physics models always combine both geometrical and thermophysical information. In other words, when calculating a physics model, data must be pulled from both an associated phase (e.g. surface tension) and the corresponding geometry (e.g. pore size). \n",
    "\n",
    "This relationship is summarized by 'the grid'.  This shows the relationship between various objects, with physics object laying at the intersection of a phase and a geometry.  \n",
    "\n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "|**The role of the Workspace and Projects is explained further** [here](/examples/tutorials/overview_of_workspace_and_projects.ipynb)|\n",
    "|**The 'grid' is particularly useful when several subdomains have been defined as demonstrated** [here](/examples/tutorials/defining_multiple_subdomains.ipynb)|\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.127775Z",
     "iopub.status.busy": "2021-06-24T11:25:02.126014Z",
     "iopub.status.idle": "2021-06-24T11:25:02.132425Z",
     "shell.execute_reply": "2021-06-24T11:25:02.133481Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+----------+----------+\n",
      "| net_01 | phase_01 | phase_02 |\n",
      "+--------+----------+----------+\n",
      "| geo_01 | ---      | phys_01  |\n",
      "+--------+----------+----------+\n"
     ]
    }
   ],
   "source": [
    "print(pn.project.grid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objects can have names\n",
    "\n",
    "The above table may be unhelpful if there are a lot of objects in the project.  This can be remedied by giving them unique names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.142054Z",
     "iopub.status.busy": "2021-06-24T11:25:02.140303Z",
     "iopub.status.idle": "2021-06-24T11:25:02.144708Z",
     "shell.execute_reply": "2021-06-24T11:25:02.143650Z"
    }
   },
   "outputs": [],
   "source": [
    "hg.name = 'mercury'\n",
    "water.name = 'water'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.155736Z",
     "iopub.status.busy": "2021-06-24T11:25:02.154107Z",
     "iopub.status.idle": "2021-06-24T11:25:02.161934Z",
     "shell.execute_reply": "2021-06-24T11:25:02.160725Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+-------+---------+\n",
      "| net_01 | water | mercury |\n",
      "+--------+-------+---------+\n",
      "| geo_01 | ---   | phys_01 |\n",
      "+--------+-------+---------+\n"
     ]
    }
   ],
   "source": [
    "print(pn.project.grid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running a simulation\n",
    "\n",
    "OpenPNM includes a large assortment of pre-written algorithms for simulating various physical processes. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performing a porosimetry simulation\n",
    "\n",
    "It is common to simulate the capillary pressure curve of a material since this is usually measured experimentally so a comparison can be made.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.177761Z",
     "iopub.status.busy": "2021-06-24T11:25:02.176378Z",
     "iopub.status.idle": "2021-06-24T11:25:02.206880Z",
     "shell.execute_reply": "2021-06-24T11:25:02.208075Z"
    }
   },
   "outputs": [],
   "source": [
    "mip = op.algorithms.Porosimetry(network=pn, phase=hg)\n",
    "mip.set_inlets(pores=pn.pores('left'))\n",
    "mip.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.230456Z",
     "iopub.status.busy": "2021-06-24T11:25:02.228807Z",
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     "shell.execute_reply": "2021-06-24T11:25:02.666624Z"
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   "source": [
    "fig = mip.plot_intrusion_curve()"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using labels to find pore indices\n",
    "\n",
    "The above simulation used ``pn.pores('left')`` during the call to ``set_inlets``.  All OpenPNM objects have a ``pores`` and a ``throats`` method that retrieves pore/throat indices if a certain label has been applied to them.\n",
    "\n",
    "|Links to Related Notebooks|\n",
    "|:-------------------------|\n",
    "|**Labels are discussed at length** [here](/examples/tutorial/using_and_creating_labels.ipynb)|\n",
    "\n",
    "Many common labels are added to networks during creation, usually indicating faces like 'left' and 'right', which are useful for applying boundary conditions.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running a fluid flow simulation\n",
    "\n",
    "Another type of simulation is to determine permeabilit of a network.  This is done using the StokesFlow algorithm.\n",
    "\n",
    "Before proceeding though, we must remember that we did not define a pore-scale hydraulic conductance model.  It is possible to assign a physics model to a phase (and geometry models to the network), but you should really know what your doing.  This is illustrated below:"
   ]
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   "source": [
    "water.add_model(propname='throat.hydraulic_conductance',\n",
    "                model=op.models.physics.hydraulic_conductance.hagen_poiseuille)"
   ]
  },
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   "source": [
    "sf = op.algorithms.StokesFlow(network=pn, phase=water)\n",
    "sf.set_value_BC(pores=pn.pores('left'), values=1)\n",
    "sf.set_value_BC(pores=pn.pores('right'), values=0)\n",
    "sf.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Altering the settings of a simulation\n",
    "\n",
    "All OpenPNM objects have a ``settings`` attribute, which is dictionary containing a variety of information about how the algorithm is run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Key                                 Value\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "name                                alg_02\n",
      "cache_A                             True\n",
      "cache_b                             True\n",
      "conductance                         throat.hydraulic_conductance\n",
      "phase                               water\n",
      "quantity                            pore.pressure\n",
      "solver_atol                         None\n",
      "solver_family                       pypardiso\n",
      "solver_max_iter                     5000\n",
      "solver_preconditioner               jacobi\n",
      "solver_rtol                         None\n",
      "solver_tol                          1e-08\n",
      "solver_type                         spsolve\n",
      "prefix                              alg\n",
      "nlin_max_iter                       5000\n",
      "relaxation_quantity                 1.0\n",
      "relaxation_source                   1.0\n",
      "sources                             []\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "print(sf.settings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimating permeability coefficient of a network\n",
    "\n",
    "Now that the fluid flow simulation has been run, its possible to determine the network's permeability by applying Darcy's law.\n",
    "\n",
    "$$ Q = \\frac{K A}{\\mu L}\\Delta P $$\n",
    "\n",
    "We know $A$ and $L$ from the network dimension, and $\\mu$ was specified as $ 0.001 Pa\\cdot s$ since we're using ``water`` as the phase.  We also applied the $\\Delta P$ as (1-0).  Therefore finding $K$ can be done algebraically once $Q$ is known.  \n",
    "\n",
    "Transport algorithms possess a ``rate`` method that calculates the rate through a set of pores.  Find the rate through one of the boundary faces can be done as:"
   ]
  },
  {
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   "execution_count": 26,
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     "shell.execute_reply": "2021-06-24T11:25:02.767371Z"
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   "source": [
    "Q = sf.rate(pores=pn.pores('left'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also know:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:02.774481Z"
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   "outputs": [],
   "source": [
    "A = Lx*Ly*spacing**2\n",
    "L = Lz*spacing\n",
    "mu = 0.001\n",
    "dP = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Therefore, the permeability coefficient for this network is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-24T11:25:02.779164Z",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.99994684e-11]\n"
     ]
    }
   ],
   "source": [
    "K = Q*mu*L/A/dP\n",
    "print(K)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Returning results to the phase object\n",
    "\n",
    "Upon running the fluid flow simulation above, the pressure in each pore is solved for.  These results are not automatically pushed back to the associated phase, and the user must explicity do so as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2021-06-24T11:25:02.788023Z"
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   },
   "outputs": [],
   "source": [
    "water.update(sf.results())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Outputting or saving simualtion results\n",
    "\n",
    "Once the simulation is complete it can be either output to Paraview as described [here](/examples/notebooks/io/rendering_in_paraview.ipynb), or saved to one of several file formats for post-processing.\n"
   ]
  }
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